Publishers face several key challenges in order to compete in today's digital environment. Users, advertisers, sponsors and content licensors require publishers to be able to deliver targeted information across multiple digital channels. In order to effectively serve users of its content, a publisher must be able to deliver the right content to the right audience at the right time. Content targeting is of value because it improves relevancy, saves time and reduces the effort required to deliver content to users. There is significant business value to publishers who develop the capability of delivering highly targeted content to a targeted audience and influence behavior.
Existing content databases from publishers have a legacy established over many years. Articles can be lengthy, consisting of 1000 or more words. Often the content has become outdated. It is a significant and expensive undertaking for a publisher to update large legacy content databases or change its data structure. Cost and effort considerations create significant barriers for publishers to adapt their legacy content to a rapidly changing and evolving digital world. To remain competitive publishers need to update and adapt content, as well as create new content types for multiple media channels such as web, mobile or social media. They must also be able to apply content targeting and behavior change models to enhance the user experience and create new business models.
To deliver a more robust digital experience that maximizes content value, publishers need to create more comprehensive and flexible content structures. Futhermore, publishers must deliver targeted content based on user behaviors, predictive behavior modeling, readiness to change mind-set and user profiles to maximize the value of content and the impact it can have.
To use a health example, a page of general health information is of low value since it is not targeted to any particular disease state. A page of content related to a specific disease (e.g. diabetes) is of medium value since it now targets a patient with diabetes. Going much further in the targeting and profiling chain, a page of content specific to a patient with diabetes, who is female, is taking medication and is ready to make a lifestyle change is of extremely high value. Moreover, the version of diabetes content delivered to a person who is ready to make a lifestyle change should be different than the diabetes content delivered to a diabetes patient who is not ready to make a lifestyle change. Publishers face many challenges to efficiently provide this level of content targeting and customization beyond the subject matter. They simply deliver diabetes content and do not consider more detailed targeting and behavior parameters. It is this additional detailed targeting around behavior models and more defined user profiles that will create a more valuable user experience and increase the value of a publisher's content.
In order to manage the complex task of organizing content databases, publishers will often use a content management system (CMS) or similar publishing system. CMS's can be effective in organizing content articles as documents. Each document, or content article, is generally stored as single block of text. Any attempt to insert targeted messages or advertisements into the editorial flow in the body of an article is done in a very clumsy manner. This creates a disconnect between the original article flow and the inserted element (these “insertions” are often done in the margins outside the boundaries of the text article or as advertisement boxes that break up an article flow). Within traditional publishing systems content articles, or documents, are tagged according to a subject matter or contextually organized based on key words within the document. In some cases publishers may employ semantic targeting of content, which is looking closer at the meaning and sense of the words in an article rather than just using key-words alone. Whether using subject, contextual or semantic methods, publishers can still only deliver associated content (or advertisements) based on a particular subject matter, key word or combination of key words. They do not provide content based on a detailed user behavior modeling or profiles. Since publishers using traditional content management systems store articles as single blocks of text they do not segment an article into components, or insert component content into the body of a text article. This approach diminishes the potential value of content, reduces readability qualities and limits the flexibility to distribute content across multiple media channels.